An aerial view of Bay Campus, with the sea stretching into the horizon.

Dr Mohammad Abedin

Senior Lecturer

Accounting and Finance

m.z.abedin@swansea.ac.uk

Office 217 - 217
Second Floor
School of Management
Bay Campus

Available For Postgraduate Supervision

Research Links

https://orcid.org/0000-0002-4688-0619

ResearchGate

Google Scholar

About

Dr. M Abedin is a Senior Lecturer in Finance (FinTech) at the School of Management, Swansea University, UK. Earlier he was a Senior Lecturer in FinTech with Teesside University, UK. Abedin has advanced analytical skills for both quantitative and qualitative research. He is an experienced data analyst and project evaluator, and specializes in fintech, data mining, and big data analytics. Abedin is actively engaged in research activities, project dissemination, guest lecturing across various disciplines nationally and internationally.

Abedin has published more than 50 SSCI and ABS listed research papers. His research works appeared on the leading peer-reviewed journals, including IEEE Transactions on Industrial Informatics, Annals of Operations Research, International Journal of Production Research, International Review of Financial Analysis, International Journal of Finance & Economics, Journal of Environmental Management, International Journal of Contemporary Hospitality Management, Information Systems Frontiers, to mention a few.

Abedin is an Associate editor of the International Review of Economics and Finance, Journal of Global Information Management, and Kybernetes. Abedin is working as a guest editor of the Decision Support Systems, Technological Forecasting & Social Change, Annals of Operations Research.

Areas Of Expertise

Fintech
Business analytics
Data analytics in finance
Sustainable finance
Energy analytics

Career Highlights

Teaching Interests

Big data in finance
Sustainable finance
Sustainable investment
Machine learning in finance
Mathematical finance
Mathematical economics
Statistics for managerial decision
Operations research
Management science

Publications

Research Highlights

Feng, Y., Abedin, M., Yin, Y., Wang, D., Cheng, E., & Coussement, K. (n.d.) An adaptive heterogeneous ensemble learning method for multi-dimensional company performance decision-making. Annals of Operations Research
https://doi.org/10.1007/s10479-024-06309-6, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67937
http://dx.doi.org/10.1007/s10479-024-06309-6
Harraki, I., Abedin, M., Belhadi, A., Kamble, S., Zkik, K., & Oudani, M. (2024). Data‐driven control and a prey–predator model for sourcing decisions in the low‐carbon intertwined supply chain. Business Strategy and the Environment, 0
https://doi.org/10.1002/bse.3971, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67579
Zeng, H., Abedin, M., Wu, R., & Ahmed, A. (2024). Asymmetric dependency among US national financial conditions and clean energy markets. Global Finance Journal
https://doi.org/10.1016/j.gfj.2024.101046, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67898
Bouteska, A., Bhuiyan, F., Sharif, T., Miftah, B., & Abedin, M. (2024). Impact of Green Bonds on Traditional Equity Markets. Research in International Business and Finance
https://doi.org/10.1016/j.ribaf.2024.102606, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67917
Abedin, M., Goldstein, M., Malhotra, N., & Yadav, M. (2024). Middle East conflict and energy companies: The effect of air and drone strikes on global energy stocks. Finance Research Letters, 69, 106009
https://doi.org/10.1016/j.frl.2024.106009, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67533

All Research

Journal Articles

Zeng, H., Huang, Q., Abedin, M., Ahmed, A., & Lucey, B. (2025). Connectedness and frequency connection among green bond, cryptocurrency and green energy-related metals around the COVID-19 outbreak. Research in International Business and Finance, 73, 102547
https://doi.org/10.1016/j.ribaf.2024.102547, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67510
Wang, Y., Sun, W., Abedin, M., Hajek, P., & Xue, W. (2025). A multi-objective lot sizing procurement model for multi-period cold chain management including supplier and carrier selection. Omega, 130, 103165
https://doi.org/10.1016/j.omega.2024.103165, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67355
Yang, F., Qiao, Y., Hajek, P., & Abedin, M. (2024). Enhancing cardiovascular risk assessment with advanced data balancing and domain knowledge-driven explainability. Expert Systems with Applications, 255, 124886
https://doi.org/10.1016/j.eswa.2024.124886, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67523
Sharif, T., Ghouli, J., Bouteska, A., & Abedin, M. (2024). The impact of COVID-19 uncertainties on energy market volatility: Evidence from the US markets. Economic Analysis and Policy, 84, 25-41.
https://doi.org/10.1016/j.eap.2024.08.008, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67434
Zeng, H., Abedin, M., & Upreti, V. (2024). Does climate risk as barometers for specific clean energy indices? Insights from quartiles and time-frequency perspective. Energy Economics, 0, 108003
https://doi.org/10.1016/j.eneco.2024.108003, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa68156
Abedin, M., Goldstein, M., Malhotra, N., & Yadav, M. (2024). Middle East conflict and energy companies: The effect of air and drone strikes on global energy stocks. Finance Research Letters, 69, 106009
https://doi.org/10.1016/j.frl.2024.106009, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67533
Bouteska, A., Gupta, A., Boden, B., & Abedin, M. (2024). Who affects CEO compensation? Firm performance, ownership structure, and board diversity. The Journal of High Technology Management Research, 35(2), 100501
https://doi.org/10.1016/j.hitech.2024.100501, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66741
Magazzino, C., Pakrooh, P., & Abedin, M. (2024). A decomposition and decoupling analysis for carbon dioxide emissions: evidence from OECD countries. Environment, Development and Sustainability, 26, 28539-28566.
https://doi.org/10.1007/s10668-023-03824-7, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa68140
Bouteska, A., Bhuiyan, F., Sharif, T., Miftah, B., & Abedin, M. (2024). Impact of Green Bonds on Traditional Equity Markets. Research in International Business and Finance
https://doi.org/10.1016/j.ribaf.2024.102606, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67917
Zeng, H., Abedin, M., Wu, R., & Ahmed, A. (2024). Asymmetric dependency among US national financial conditions and clean energy markets. Global Finance Journal
https://doi.org/10.1016/j.gfj.2024.101046, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67898
Yang, F., Abedin, M., Qiao, Y., & Ye, L. (2024). Towards Trustworthy Governance of AI-Generated Content (AIGC): A Blockchain-Driven Regulatory Framework for Secure Digital Ecosystems. IEEE Transactions on Engineering Management, 71, 14945-14962.
https://doi.org/10.1109/tem.2024.3472292, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67990
Abedin, M., Goldstein, M., Huang, Q., & Zeng, H. (2024). Forward-looking disclosure effects on stock liquidity in China: Evidence from MD&A text analysis. International Review of Financial Analysis, 95, 103484
https://doi.org/10.1016/j.irfa.2024.103484, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67257
Adu, D., Abedin, M., Saa, V., & Boateng, F. (2024). Bank sustainability, climate change initiatives and financial performance: The role of corporate governance. International Review of Financial Analysis, 95, 103438
https://doi.org/10.1016/j.irfa.2024.103438, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66973
Harraki, I., Abedin, M., Belhadi, A., Kamble, S., Zkik, K., & Oudani, M. (2024). Data‐driven control and a prey–predator model for sourcing decisions in the low‐carbon intertwined supply chain. Business Strategy and the Environment, 0
https://doi.org/10.1002/bse.3971, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67579
Coussement, K., Abedin, M., Kraus, M., Maldonado, S., & Topuz, K. (2024). Explainable AI for enhanced decision-making. Decision Support Systems, 184, 114276
https://doi.org/10.1016/j.dss.2024.114276, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66910
Yang, F., Abedin, M., & Hajek, P. (2024). An explainable federated learning and blockchain-based secure credit modeling method. European Journal of Operational Research, 317(2)
https://doi.org/10.1016/j.ejor.2023.08.040, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64204
http://dx.doi.org/10.1016/j.ejor.2023.08.040
Xia, H., Hou, X., Zhang, J., & Abedin, M. (2024). A new probability forecasting model for cotton yarn futures price volatility with explainable AI and big data. Journal of Forecasting, 0
https://doi.org/10.1002/for.3185, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67179
Zeng, H., Abedin, M., & Ahmed, A. (2024). Quartile risk dependence between clean energy markets and the U.S. travel and leisure index. Current Issues in Tourism, 0, 1-25.
https://doi.org/10.1080/13683500.2024.2381716, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67180
Wu, Y., Ofori, E., Tao, L., Lucey, B., & Abedin, M. (2024). Combination of antecedent conditions affecting the development of Chinese new energy market based on fuzzy sets. Research in International Business and Finance, 71, 102453
https://doi.org/10.1016/j.ribaf.2024.102453, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66811
Efat, M., Hajek, P., Abedin, M., Azad, R., Jaber, M., Aditya, S., & Hassan, M. (2024). Deep-learning model using hybrid adaptive trend estimated series for modelling and forecasting sales. Annals of Operations Research, 339, 297-328.
https://doi.org/10.1007/s10479-022-04838-6, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64231
Hasan, M., Hoque, A., Abedin, M., & Gasbarro, D. (2024). FinTech and sustainable development: A systematic thematic analysis using human- and machine-generated processing. International Review of Financial Analysis, 0, 103473
https://doi.org/10.1016/j.irfa.2024.103473, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67255
Liu, X., Zhao, N., Wei, W., & Abedin, M. (2024). Diffusion prediction of competitive information with time-varying attractiveness in social networks. Information Processing and Management, 61(4), 103739
https://doi.org/10.1016/j.ipm.2024.103739, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66205
Liu, Z., Zhang, Y., Abedin, M., Wang, J., Yang, H., Gao, Y., & Chen, Y. (2024). Profit-driven fusion framework based on bagging and boosting classifiers for potential purchaser prediction. Journal of Retailing and Consumer Services, 79, 103854
https://doi.org/10.1016/j.jretconser.2024.103854, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66109
Che, W., Wang, Z., Jiang, C., & Abedin, M. (2024). Predicting financial distress using multimodal data: An attentive and regularized deep learning method. Information Processing and Management, 61(4), 103703
https://doi.org/10.1016/j.ipm.2024.103703, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65837
Zhang, L., Abedin, M., & Liu, Z. (2024). Incorporating media news to predict financial distress: Case study on Chinese listed companies. Journal of Forecasting, 43(5), 1374-1398.
https://doi.org/10.1002/for.3089, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65654
Bouteska, A., Sharif, T., & Abedin, M. (2024). Does investor sentiment create value for asset pricing? An empirical investigation of the KOSPI-listed firms. International Journal of Finance and Economics, 29(3), 3487-3509.
https://doi.org/10.1002/ijfe.2836, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63609
Zhao, X., Benkraiem, R., Zhou, S., & Abedin, M. (2024). The charm of green finance: Can green finance reduce corporate carbon emissions?. Energy Economics, 134, 107574
https://doi.org/10.1016/j.eneco.2024.107574, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66204
Zeng, H., Abedin, M., & Lucey, B. (2024). Heterogeneous dependence of the FinTech Index with Global Systemically Important Banks (G-SIBs). Finance Research Letters, 64, 105424
https://doi.org/10.1016/j.frl.2024.105424, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66153
Bouteska, A., Sharif, T., Hajek, P., & Abedin, M. (2024). Aversion and ambiguity: On the robustness of the macroeconomic uncertainty measure framework. Technological Forecasting and Social Change, 203, 123340
https://doi.org/10.1016/j.techfore.2024.123340, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66084
Bouteska, A., Ha, L., Bhuiyan, F., Sharif, T., & Abedin, M. (2024). Contagion between investor sentiment and green bonds in China during the global uncertainties. International Review of Economics and Finance, 93, 469-484.
https://doi.org/10.1016/j.iref.2024.03.045, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65957
Jiang, P., Liu, Z., Abedin, M., Wang, J., Yang, W., & Dong, Q. (2024). Profit-driven weighted classifier with interpretable ability for customer churn prediction. Omega, 125, 103034
https://doi.org/10.1016/j.omega.2024.103034, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65447
Chai, N., Abedin, M., Wang, X., & Shi, B. (2024). Growth potential of machine learning in credit risk predicting of farmers in the industry 4.0 era. International Journal of Finance & Economics, 0
https://doi.org/10.1002/ijfe.3010, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66567
Gao, R., Yao, X., Wang, Z., & Abedin, M. (2024). Sentiment classification of time-sync comments: A semi-supervised hierarchical deep learning method. European Journal of Operational Research, 314(3), 1159-1173.
https://doi.org/10.1016/j.ejor.2023.11.035, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65091
Bouteska, A., Sharif, T., Abedin, M., & Abedin, M. (2024). Executive compensation, risk and performance: evidence from the USA. Corporate Governance: The International Journal of Business in Society, 24(4), 964-991.
https://doi.org/10.1108/cg-01-2023-0017, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65426
http://dx.doi.org/10.1108/cg-01-2023-0017
Wang, X., Han, Y., Shi, B., & Abedin, M. (2024). The impacts of green credit guidelines on total factor productivity of heavy-polluting enterprises: A quasi-natural experiment from China. Annals of Operations Research, 0
https://doi.org/10.1007/s10479-024-05973-y, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66133
Bouteska, A., Sharif, T., Bhuiyan, F., & Abedin, M. (2024). Impacts of the changing climate on agricultural productivity and food security: Evidence from Ethiopia. Journal of Cleaner Production, 449
https://doi.org/10.1016/j.jclepro.2024.141793, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65844
Yang, F., Qiao, Y., Bo, J., Ye, L., & Abedin, M. (2024). Blockchain and Digital Asset Transactions- Based Carbon Emissions Trading Scheme for Industrial Internet of Things. IEEE Transactions on Industrial Informatics, 20(4), 6963-6973.
https://doi.org/10.1109/tii.2024.3354338, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65540
Ha, L., Bouteska, A., Sharif, T., & Abedin, M. (2024). Dynamic interlinkages between carbon risk and volatility of green and renewable energy: A TVP-VAR analysis. Research in International Business and Finance, 69
https://doi.org/10.1016/j.ribaf.2024.102278, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65711
Belhadi, A., Venkatesh, M., Kamble, S., & Abedin, M. (2024). Data-driven digital transformation for supply chain carbon neutrality: Insights from cross-sector supply chain. International Journal of Production Economics, 270
https://doi.org/10.1016/j.ijpe.2024.109178, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65698
Abdou, H., Elamer, A., Abedin, M., & Ibrahim, B. (2024). The impact of oil and global markets on Saudi stock market predictability: A machine learning approach. Energy Economics, 132
https://doi.org/10.1016/j.eneco.2024.107416, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65694
Khurram, M., Chen, L., Abedin, M., Adu, D., & Lucey, B. (2024). ESG disclosure and internal pay gap: Empirical evidence from China. International Review of Economics and Finance, 92, 228-244.
https://doi.org/10.1016/j.iref.2024.02.023, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65637
Zeng, H., Abedin, M., Zhou, X., & Lu, R. (2024). Measuring the extreme linkages and time-frequency co-movements among artificial intelligence and clean energy indices. International Review of Financial Analysis, 92, 103073
https://doi.org/10.1016/j.irfa.2024.103073, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65445
Wang, Y., Liu, S., Abedin, M., & Lucey, B. (2024). Volatility spillover and hedging strategies among Chinese carbon, energy, and electricity markets. Journal of International Financial Markets, Institutions and Money, 91, 101938
https://doi.org/10.1016/j.intfin.2024.101938, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65422
Bouteska, A., Abedin, M., Hajek, P., & Yuan, K. (2024). Cryptocurrency price forecasting – A comparative analysis of ensemble learning and deep learning methods. International Review of Financial Analysis, 92, 103055
https://doi.org/10.1016/j.irfa.2023.103055, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65393
Mozumder, S., Abedin, M., Lalon, R., & Hossain, A. (2024). Which User-Friendly Model is the Best for BASEL-III? An Emerging Market Study. Computational Economics, 0
https://doi.org/10.1007/s10614-023-10545-6, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65719
Yadav, M., Abedin, M., Sinha, N., & Arya, V. (2024). Uncovering dynamic connectedness of Artificial intelligence stocks with agri-commodity market in wake of COVID-19 and Russia-Ukraine Invasion. Research in International Business and Finance, 67, 102146
https://doi.org/10.1016/j.ribaf.2023.102146, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64915
http://dx.doi.org/10.1016/j.ribaf.2023.102146
Hoque, A., Le, T., Hasan, M., & Abedin, M. (2024). Does market efficiency matter for Shanghai 50 ETF index options?. Research in International Business and Finance, 67, 102129
https://doi.org/10.1016/j.ribaf.2023.102129, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64761
http://dx.doi.org/10.1016/j.ribaf.2023.102129
Chai, S., Li, Q., Abedin, M., & Lucey, B. (2024). Forecasting electricity prices from the state-of-the-art modeling technology and the price determinant perspectives. Research in International Business and Finance, 67, 102132
https://doi.org/10.1016/j.ribaf.2023.102132, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64760
http://dx.doi.org/10.1016/j.ribaf.2023.102132
Uddin, M., Sharif, T., Islam, A., & Abedin, M. (2024). Moderating impact of FDI on the growth-environment nexus in the pre-COVID-19 eras. Research in International Business and Finance, 67, 102114
https://doi.org/10.1016/j.ribaf.2023.102114, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64661
http://dx.doi.org/10.1016/j.ribaf.2023.102114
Belanes, A., Saâdaoui, F., & Abedin, M. (2024). Potential diversification benefits: A comparative study of Islamic and conventional stock market indexes. Research in International Business and Finance, 67, 102098
https://doi.org/10.1016/j.ribaf.2023.102098, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64516
http://dx.doi.org/10.1016/j.ribaf.2023.102098
Hasan, M., Abedin, M., Hajek, P., Coussement, K., Sultan, M., & Lucey, B. (2024). A blending ensemble learning model for crude oil price forecasting. Annals of Operations Research, 0
https://doi.org/10.1007/s10479-023-05810-8, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65513
Goodell, J., Yadav, M., Ruan, J., Abedin, M., & Malhotra, N. (2023). Traditional assets, digital assets and renewable energy: Investigating connectedness during COVID-19 and the Russia-Ukraine war. Finance Research Letters, 58(A), 104323
https://doi.org/10.1016/j.frl.2023.104323, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64238
http://dx.doi.org/10.1016/j.frl.2023.104323
Moktadir, M., Sarker, M., Sharif, T., & Abedin, M. (2023). A decision support model to investigate the pandemic recovery challenges and strategies in the leather supply chain. Annals of Operations Research, 0
https://doi.org/10.1007/s10479-023-05708-5, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65380
http://dx.doi.org/10.1007/s10479-023-05708-5
Munmun, S., Moktadir, M., Tiwari, S., Abedin, M., & Jabbour, C. (2023). Investigation of key performance indicators for performance management of the manufacturing industry in the era of the COVID-19 pandemic. Annals of Operations Research, 0
https://doi.org/10.1007/s10479-023-05717-4, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65274
Chai, N., Gong, Z., Bai, C., Abedin, M., & Shi, B. (2023). A socio-technology perspective for building a Chinese regional green economy. Annals of Operations Research
https://doi.org/10.1007/s10479-023-05719-2, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65187
Bouteska, A., Seranto, M., Hajek, P., & Abedin, M. (2023). Data-driven decadal climate forecasting using Wasserstein time-series generative adversarial networks. Annals of Operations Research, 0
https://doi.org/10.1007/s10479-023-05722-7, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65186
Wei, W., Han, Y., Abedin, M., Ma, J., & Chai, S. (2023). Empirical study on the technical efficiency and total factor productivity of power industry: Evidence from Chinese provinces. Energy Economics, 128, 107161
https://doi.org/10.1016/j.eneco.2023.107161, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64936
Chai, S., Zhang, X., Abedin, M., Chen, H., Lucey, B., & Hajek, P. (2023). An optimized GRT model with blockchain digital smart contracts for power generation enterprises. Energy Economics, 128, 107153
https://doi.org/10.1016/j.eneco.2023.107153, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64913
Wang, X., Zhang, T., Luo, S., & Abedin, M. (2023). Pathways to improve energy efficiency under carbon emission constraints in iron and steel industry: Using EBM, NCA and QCA approaches. Journal of Environmental Management, 348, 119206
https://doi.org/10.1016/j.jenvman.2023.119206, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64832
http://dx.doi.org/10.1016/j.jenvman.2023.119206
Bouteska, A., Sharif, T., & Abedin, M. (2023). Volatility spillovers and other dynamics between cryptocurrencies and the energy and bond markets. The Quarterly Review of Economics and Finance, 92, 1-13.
https://doi.org/10.1016/j.qref.2023.07.008, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64239
Ding, S., Cui, T., Bellotti, A., Abedin, M., & Lucey, B. (2023). The role of feature importance in predicting corporate financial distress in pre and post COVID periods: Evidence from China. International Review of Financial Analysis, 90, 102851
https://doi.org/10.1016/j.irfa.2023.102851, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64218
http://dx.doi.org/10.1016/j.irfa.2023.102851
Adu, D., Abedin, M., & Hasan, M. (2023). Bank ownership structures and sustainable banking initiatives: The moderating effect of governance mechanism. International Review of Financial Analysis, 89, 102736
https://doi.org/10.1016/j.irfa.2023.102736, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64219
http://dx.doi.org/10.1016/j.irfa.2023.102736
Bouteska, A., Harasheh, M., & Abedin, M. (2023). Revisiting Overconfidence In Investment Decision-Making: Further Evidence From The U.S. Market. Research in International Business and Finance, 66, 102028
https://doi.org/10.1016/j.ribaf.2023.102028, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63950
http://dx.doi.org/10.1016/j.ribaf.2023.102028
Maheshwari, P., Kamble, S., Belhadi, A., Venkatesh, M., & Abedin, M. (2023). Digital twin-driven real-time planning, monitoring, and controlling in food supply chains. Technological Forecasting and Social Change, 195, 122799
https://doi.org/10.1016/j.techfore.2023.122799, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64158
http://dx.doi.org/10.1016/j.techfore.2023.122799
Wang, D., Wang, X., Abedin, M., Wang, S., & Yin, Y. (2023). Interpretable multi-hop knowledge reasoning for gastrointestinal disease. Annals of Operations Research, 0
https://doi.org/10.1007/s10479-023-05650-6, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64914
Hajek, P., Abedin, M., & Sivarajah, U. (2023). Fraud Detection in Mobile Payment Systems using an XGBoost-based Framework. Information Systems Frontiers, 25, 1985-2003.
https://doi.org/10.1007/s10796-022-10346-6, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64228
Ahmed, S., Ting, D., Sharif, T., & Abedin, M. (2023). Implication of ‘camera eats first’ construct: unraveling the potentials of digital images in social media on information sharing. Electronic Commerce Research
https://doi.org/10.1007/s10660-023-09737-x, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64375
Abedin, M., Guotai, C., Hajek, P., & Zhang, T. (2023). Combining weighted SMOTE with ensemble learning for the class-imbalanced prediction of small business credit risk. Complex and Intelligent Systems, 9(4), 3559-3579.
https://doi.org/10.1007/s40747-021-00614-4, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64260
http://dx.doi.org/10.1007/s40747-021-00614-4
Chen, S., Bouteska, A., Sharif, T., & Abedin, M. (2023). The Russia–Ukraine war and energy market volatility: A novel application of the volatility ratio in the context of natural gas. Resources Policy, 85(A), 103792
https://doi.org/10.1016/j.resourpol.2023.103792, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64240
http://dx.doi.org/10.1016/j.resourpol.2023.103792
Ghosh, I., Jana, R., & Abedin, M. (2023). An ensemble machine learning framework for Airbnb rental price modeling without using amenity-driven features. International Journal of Contemporary Hospitality Management, 35(10), 3592-3611.
https://doi.org/10.1108/ijchm-05-2022-0562, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64223
http://dx.doi.org/10.1108/ijchm-05-2022-0562
Yadav, M., Rao, A., Abedin, M., Tabassum, S., & Lucey, B. (2023). The domino effect: Analyzing the impact of Silicon Valley Bank's fall on top equity indices around the world. Finance Research Letters, 55, 103952
https://doi.org/10.1016/j.frl.2023.103952, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64241
http://dx.doi.org/10.1016/j.frl.2023.103952
Chandrika, R., Sharif, T., Mahesh, R., Yadav, M., & Abedin, M. (2023). Do market, resource and knowledge distance impact inbound cross-border acquisition?. Global Finance Journal, 57, 100862
https://doi.org/10.1016/j.gfj.2023.100862, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63704
http://dx.doi.org/10.1016/j.gfj.2023.100862
Hasan, M., Noor, T., Gao, J., Usman, M., & Abedin, M. (2023). Rural Consumers’ Financial Literacy and Access to FinTech Services. Journal of the Knowledge Economy, 14(2), 780-804.
https://doi.org/10.1007/s13132-022-00936-9, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64257
http://dx.doi.org/10.1007/s13132-022-00936-9
Hasan, M., Abedin, M., Amin, M., Nekmahmud, M., & Oláh, J. (2023). Sustainable biofuel economy: A mapping through bibliometric research. Journal of Environmental Management, 336, 117644
https://doi.org/10.1016/j.jenvman.2023.117644, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64224
http://dx.doi.org/10.1016/j.jenvman.2023.117644
Chowdhury, M., Abdullah, M., Alam, M., Abedin, M., & Shi, B. (2023). NFTs, DeFi, and other assets efficiency and volatility dynamics: An asymmetric multifractality analysis. International Review of Financial Analysis, 87, 102642
https://doi.org/10.1016/j.irfa.2023.102642, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64221
http://dx.doi.org/10.1016/j.irfa.2023.102642
Zhao, Y., Goodell, J., Wang, Y., & Abedin, M. (2023). Fintech, macroprudential policies and bank risk: Evidence from China. International Review of Financial Analysis, 87, 102648
https://doi.org/10.1016/j.irfa.2023.102648, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64220
http://dx.doi.org/10.1016/j.irfa.2023.102648
Abedin, M., Hajek, P., Sharif, T., Satu, M., & Khan, M. (2023). Modelling bank customer behaviour using feature engineering and classification techniques. Research in International Business and Finance, 65, 101913
https://doi.org/10.1016/j.ribaf.2023.101913, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64243
http://dx.doi.org/10.1016/j.ribaf.2023.101913
Yadav, M., Sharif, T., Ashok, S., Dhingra, D., & Abedin, M. (2023). Investigating volatility spillover of energy commodities in the context of the Chinese and European stock markets. Research in International Business and Finance, 65, 101948
https://doi.org/10.1016/j.ribaf.2023.101948, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64242
http://dx.doi.org/10.1016/j.ribaf.2023.101948
Ahmed, T., Rahman, M., Aktar, M., Gupta, A., & Abedin, M. (2023). The impact of economic development on environmental sustainability: evidence from the Asian region. Environment, Development and Sustainability, 25(4), 3523-3553.
https://doi.org/10.1007/s10668-022-02178-w, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64273
http://dx.doi.org/10.1007/s10668-022-02178-w
Wang, X., Lu, C., Cao, Y., Chen, L., & Abedin, M. (2023). Decomposition, decoupling, and future trends of environmental effects in the Beijing-Tianjin-Hebei region: A regional heterogeneity-based analysis. Journal of Environmental Management, 331, 117124
https://doi.org/10.1016/j.jenvman.2022.117124, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64225
http://dx.doi.org/10.1016/j.jenvman.2022.117124
Chen, L., Abedin, M., Gao, Y., Abedin, M., & Lucey, B. (2023). ESG disclosure and technological innovation capabilities of the Chinese listed companies. Research in International Business and Finance, 65, 101974
https://doi.org/10.1016/j.ribaf.2023.101974, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63248
http://dx.doi.org/10.1016/j.ribaf.2023.101974
Dharani, M., Hassan, M., Huda, M., & Abedin, M. (2023). Covid-19 pandemic and stock returns in India. Journal of Economics and Finance, 47(1), 251-266.
https://doi.org/10.1007/s12197-022-09586-8, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64278
http://dx.doi.org/10.1007/s12197-022-09586-8
Nurmakhanova, M., Elheddad, M., Alfar, A., Egbulonu, A., & Abedin, M. (2023). Does natural resource curse in finance exist in Africa? Evidence from spatial techniques. Resources Policy, 80, 103151
https://doi.org/10.1016/j.resourpol.2022.103151, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64248
http://dx.doi.org/10.1016/j.resourpol.2022.103151
Bouteska, A., Hajek, P., Fisher, B., & Abedin, M. (2023). Nonlinearity in forecasting energy commodity prices: Evidence from a focused time-delayed neural network. Research in International Business and Finance, 64, 101863
https://doi.org/10.1016/j.ribaf.2022.101863, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64246
http://dx.doi.org/10.1016/j.ribaf.2022.101863
Bouteska, A., Hajek, P., Abedin, M., & Dong, Y. (2023). Effect of twitter investor engagement on cryptocurrencies during the COVID-19 pandemic. Research in International Business and Finance, 64, 101850
https://doi.org/10.1016/j.ribaf.2022.101850, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64245
http://dx.doi.org/10.1016/j.ribaf.2022.101850
Bouteska, A., Sharif, T., & Abedin, M. (2023). COVID-19 and stock returns: Evidence from the Markov switching dependence approach. Research in International Business and Finance, 64, 101882
https://doi.org/10.1016/j.ribaf.2023.101882, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64244
http://dx.doi.org/10.1016/j.ribaf.2023.101882
Sahoo, S., Kumar, S., Abedin, M., Lim, W., & Jakhar, S. (2023). Deep learning applications in manufacturing operations: a review of trends and ways forward. Journal of Enterprise Information Management, 36(1), 221-251.
https://doi.org/10.1108/jeim-01-2022-0025, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64251
http://dx.doi.org/10.1108/jeim-01-2022-0025
Dhifaoui, Z., Khalfaoui, R., Jabeur, S., & Abedin, M. (2023). Exploring the effect of climate risk on agricultural and food stock prices: Fresh evidence from EMD-Based variable-lag transfer entropy analysis. Journal of Environmental Management, 326, 116789
https://doi.org/10.1016/j.jenvman.2022.116789, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64226
http://dx.doi.org/10.1016/j.jenvman.2022.116789
Shajalal, M., Hajek, P., & Abedin, M. (2023). Product backorder prediction using deep neural network on imbalanced data. International Journal of Production Research, 61(1), 302-319.
https://doi.org/10.1080/00207543.2021.1901153, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64236
http://dx.doi.org/10.1080/00207543.2021.1901153
Rahman, M., Guotai, C., Gupta, A., Hossain, M., & Abedin, M. (2022). Impact of early COVID-19 pandemic on the US and European stock markets and volatility forecasting. Economic Research-Ekonomska Istraživanja, 35(1), 3591-3608.
https://doi.org/10.1080/1331677x.2021.1997626, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64263
http://dx.doi.org/10.1080/1331677x.2021.1997626
Chai, S., Yang, X., Zhang, Z., Abedin, M., & Lucey, B. (2022). Regional imbalances of market efficiency in China’s pilot emission trading schemes (ETS): A multifractal perspective. Research in International Business and Finance, 63, 101758
https://doi.org/10.1016/j.ribaf.2022.101758, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64247
http://dx.doi.org/10.1016/j.ribaf.2022.101758
Yang, F., Qiao, Y., Abedin, M., & Huang, C. (2022). Privacy-Preserved Credit Data Sharing Integrating Blockchain and Federated Learning for Industrial 4.0. IEEE Transactions on Industrial Informatics, 18(12), 8755-8764.
https://doi.org/10.1109/tii.2022.3151917, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64232
http://dx.doi.org/10.1109/tii.2022.3151917
Khalfaoui, R., Mefteh-Wali, S., Viviani, J., Jabeur, S., Abedin, M., & Lucey, B. (2022). How do climate risk and clean energy spillovers, and uncertainty affect U.S. stock markets?. Technological Forecasting and Social Change, 185, 122083
https://doi.org/10.1016/j.techfore.2022.122083, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64229
http://dx.doi.org/10.1016/j.techfore.2022.122083
Saini, N., Singhania, M., Hasan, M., Yadav, M., & Abedin, M. (2022). Non-financial disclosures and sustainable development: A scientometric analysis. Journal of Cleaner Production, 381(1), 135173
https://doi.org/10.1016/j.jclepro.2022.135173, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64255
http://dx.doi.org/10.1016/j.jclepro.2022.135173
Sana, J., Abedin, M., Rahman, M., & Rahman, M. (2022). A novel customer churn prediction model for the telecommunication industry using data transformation methods and feature selection. PLOS ONE, 17(12), e0278095
https://doi.org/10.1371/journal.pone.0278095, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64261
http://dx.doi.org/10.1371/journal.pone.0278095
Zhao, Y., Goodell, J., Dong, Q., Wang, Y., & Abedin, M. (2022). Overcoming spatial stratification of fintech inclusion: Inferences from across Chinese provinces to guide policy makers. International Review of Financial Analysis, 84, 102411
https://doi.org/10.1016/j.irfa.2022.102411, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64227
http://dx.doi.org/10.1016/j.irfa.2022.102411
Dhifaoui, Z., Khalfaoui, R., Abedin, M., & Shi, B. (2022). Quantifying information transfer among clean energy, carbon, oil, and precious metals: A novel transfer entropy-based approach. Finance Research Letters, 49, 103138
https://doi.org/10.1016/j.frl.2022.103138, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64249
http://dx.doi.org/10.1016/j.frl.2022.103138
Chai, S., Zhang, K., Wei, W., Ma, W., & Abedin, M. (2022). The impact of green credit policy on enterprises' financing behavior: Evidence from Chinese heavily-polluting listed companies. Journal of Cleaner Production, 363, 132458
https://doi.org/10.1016/j.jclepro.2022.132458, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64256
http://dx.doi.org/10.1016/j.jclepro.2022.132458
Moudud-Ul-Huq, S., Biswas, T., Halim, M., Mateev, M., Yousaf, I., & Abedin, M. (2022). The effects of bank competition, financial stability and ownership structure: evidence from the Middle East and North African (MENA) countries. International Journal of Islamic and Middle Eastern Finance and Management, 15(4), 717-738.
https://doi.org/10.1108/imefm-05-2020-0214, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64254
http://dx.doi.org/10.1108/imefm-05-2020-0214
Abedin, M., Hassan, M., Khan, I., & Julio, I. (2022). Feature Transformation for Corporate Tax Default Prediction: Application of Machine Learning Approaches. Asia-Pacific Journal of Operational Research, 39(04)
https://doi.org/10.1142/s0217595921400170, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64276
http://dx.doi.org/10.1142/s0217595921400170
Sunny, F., Hajek, P., Munk, M., Abedin, M., Satu, M., Efat, M., & Islam, M. (2022). A Systematic Review of Blockchain Applications. IEEE Access, 10, 59155-59177.
https://doi.org/10.1109/access.2022.3179690, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64262
http://dx.doi.org/10.1109/access.2022.3179690
Sureka, R., Kumar, S., Colombage, S., & Abedin, M. (2022). Five decades of research on capital budgeting – A systematic review and future research agenda. Research in International Business and Finance, 60, 101609
https://doi.org/10.1016/j.ribaf.2021.101609, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64250
http://dx.doi.org/10.1016/j.ribaf.2021.101609
Dharani, M., Hassan, M., Abedin, M., & Ismail, M. (2022). Does a search attention index explain portfolio returns in India?. Borsa Istanbul Review, 22(2), 226-239.
https://doi.org/10.1016/j.bir.2021.04.003, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64270
http://dx.doi.org/10.1016/j.bir.2021.04.003
Rahman, M., Ahmed, R., Mashud, A., Malik, A., Miah, S., & Abedin, M. (2022). Consumption-Based CO2 Emissions on Sustainable Development Goals of SAARC Region. Sustainability, 14(3), 1467
https://doi.org/10.3390/su14031467, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64268
http://dx.doi.org/10.3390/su14031467
Abedin, M., Moon, M., Hassan, M., & Hajek, P. (2021). Deep learning-based exchange rate prediction during the COVID-19 pandemic. Annals of Operations Research
https://doi.org/10.1007/s10479-021-04420-6, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64234
http://dx.doi.org/10.1007/s10479-021-04420-6
Aktar, M., Abedin, M., & Gupta, A. (2021). The Impact of Monetary Policy Shocks on Corporate Dynamic Investment Activity With Financial Heterogeneity. Sage Open, 11(1), 215824402098868
https://doi.org/10.1177/2158244020988683, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64274
http://dx.doi.org/10.1177/2158244020988683
Abedin, M., Chi, G., Uddin, M., Satu, M., Khan, M., & Hajek, P. (2021). Tax Default Prediction Using Feature Transformation-Based Machine Learning. IEEE Access, 9, 19864-19881.
https://doi.org/10.1109/access.2020.3048018, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64271
http://dx.doi.org/10.1109/access.2020.3048018
Hajek, P. & Abedin, M. (2020). A Profit Function-Maximizing Inventory Backorder Prediction System Using Big Data Analytics. IEEE Access, 8, 58982-58994.
https://doi.org/10.1109/access.2020.2983118, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64272
http://dx.doi.org/10.1109/access.2020.2983118
Chi, G., Uddin, M., Abedin, M., & Yuan, K. (2019). Hybrid Model for Credit Risk Prediction: An Application of Neural Network Approaches. International Journal on Artificial Intelligence Tools, 28(05), 1950017
https://doi.org/10.1142/s0218213019500179, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64277
http://dx.doi.org/10.1142/s0218213019500179
Abedin, M., Guotai, C., Moula, F., Zhang, T., & Hassan, M. (2019). An optimized support vector machine intelligent technique using optimized feature selection methods: evidence from Chinese credit approval data. Journal of Risk Model Validation, 13(2), 1-46.
https://doi.org/10.21314/jrmv.2019.206, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64258
http://dx.doi.org/10.21314/jrmv.2019.206
Abedin, M., Guotai, C., Moula, F., Azad, A., & Khan, M. (2019). Topological applications of multilayer perceptrons and support vector machines in financial decision support systems. International Journal of Finance & Economics, 24(1), 474-507.
https://doi.org/10.1002/ijfe.1675, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64237
http://dx.doi.org/10.1002/ijfe.1675
Abedin, M., Guotai, C., Colombage, S., & Moula, F. (2018). Credit default prediction using a support vector machine and a probabilistic neural network. Journal of Credit Risk, 14(2), 1-27.
https://doi.org/10.21314/jcr.2017.233, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64259
http://dx.doi.org/10.21314/jcr.2017.233
Moula, F., Guotai, C., & Abedin, M. (2017). Credit default prediction modeling: an application of support vector machine. Risk Management, 19(2), 158-187.
https://doi.org/10.1057/s41283-017-0016-x, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64269
http://dx.doi.org/10.1057/s41283-017-0016-x
Feng, Y., Abedin, M., Yin, Y., Wang, D., Cheng, E., & Coussement, K. (n.d.) An adaptive heterogeneous ensemble learning method for multi-dimensional company performance decision-making. Annals of Operations Research
https://doi.org/10.1007/s10479-024-06309-6, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67937
http://dx.doi.org/10.1007/s10479-024-06309-6
Lv, L., Fan, L., Meng, B., Abedin, M., & Feng, H. (n.d.) A Combined Evaluation Method of Corporate Social Responsibility Based on the Difference and Similarity: A Case Study of Transportation Industry in China. Sustainability, 15(6), 5561
https://doi.org/10.3390/su15065561, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64279
http://dx.doi.org/10.3390/su15065561
GUOTAI, C., Abedin, M., & E–MOULA, F. (n.d.) MODELING CREDIT APPROVAL DATA WITH NEURAL NETWORKS: AN EXPERIMENTAL INVESTIGATION AND OPTIMIZATION. Journal of Business Economics and Management, 18(2), 224-240.
https://doi.org/10.3846/16111699.2017.1280844, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64252
http://dx.doi.org/10.3846/16111699.2017.1280844
Chai, S., Chu, W., Zhang, Z., Li, Z., & Abedin, M. (n.d.) Dynamic nonlinear connectedness between the green bonds, clean energy, and stock price: the impact of the COVID-19 pandemic. Annals of Operations Research
https://doi.org/10.1007/s10479-021-04452-y, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64233
http://dx.doi.org/10.1007/s10479-021-04452-y
Lu, Y., Yang, L., Shi, B., Li, J., & Abedin, M. (n.d.) A novel framework of credit risk feature selection for SMEs during industry 4.0. Annals of Operations Research
https://doi.org/10.1007/s10479-022-04849-3, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64230
http://dx.doi.org/10.1007/s10479-022-04849-3
Yang, C., Abedin, M., Zhang, H., Weng, F., & Hajek, P. (n.d.) An interpretable system for predicting the impact of COVID-19 government interventions on stock market sectors. Annals of Operations Research
https://doi.org/10.1007/s10479-023-05311-8, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64222

Edited Books

Abedin, M. & Hajek, P. (Eds.). (2023). Cyber Security and Business Intelligence: Innovations and Machine Learning for Cyber Risk Management. Routledge.
https://doi.org/10.4324/9781003285854, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64982
Abedin, M. & Hajek, P. (Eds.). (2023). Novel Financial Applications of Machine Learning and Deep Learning: Algorithms, Product Modeling, and Applications. Springer Nature Switzerland.
https://doi.org/10.1007/978-3-031-18552-6, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64280

Supervision

Untitled (current)

PhD

Other supervisor: Dr Sarosh Shabi
Untitled (current)

MSc

Other supervisor: Dr Vineet Upreti

Taught Modules

MN-M584 Big Data in Finance

Big Data analytics is increasingly desired by various businesses in today¿s data-driven landscape. The main goal of this module is to provide students with skills in collecting, handling, managing, analysing and making initial inferences in the process of discovering patterns in large data sets. The data management and statistical software used in this module are all very useful for prospective jobs in Data Analytics in Finance, Business, and other industries.
MN-M609 Sustainable Finance and ESG Investing

Sustainable investing is a topic of increasing interest to the financial community. With global environmental and social challenges increasing, trillions of dollars are beginning to shift into investments which meet the challenges. This module provides students with the insight, knowledge and tools they will need to become an important part of this global shift in investing practice.